System and method for improving the quality of halftone video using an adaptive threshold

ABSTRACT

A system and method for processing video data are disclosed. In one aspect, a method includes generating halftone data for a first video frame and generating halftone data for a second video frame. The method further includes, to reduce at least one visual artifact, selectively copying the halftone data for the first video frame into the halftone data for the second video frame, the selectively copying being based upon a comparison between an adaptive threshold and the change resulting due to the copying of the data, in the human visual system model-based perceptual error of the halftone data for the second video frame.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of PCT Application No. PCT/U.S. Ser. No. 10/37315, filed Jun. 3, 2010, which claims priority under 35 U.S.C. Section 119(e) to U.S. Provisional Application No. 61/184,537 filed on Jun. 5, 2009. This application claims priority under 35 U.S.C. Section 119(e) to U.S. Provisional Application No. 61/184,537 filed on Jun. 5, 2009. This application is related to U.S. Application Ser. No. ______ (attorney docket No: QCO.272A), filed concurrently herewith and titled “SYSTEM AND METHOD FOR IMPROVING THE QUALITY OF HALFTONE VIDEO USING A FIXED THRESHOLD.” Each of the above applications is incorporated by reference hereby in its entirety.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The field of the invention relates to image processing.

2. Description of the Related Technology

Halftoning is a technique that transforms continuous-tone images into binary images. When a continuous-tone video stream needs to be shown on a binary display, a halftone video may be produced by halftoning each frame in the video stream independently. However, this process results in artifacts including flicker, i.e., an artifact between frames that occurs on the display at low refresh rates. Therefore, it is desirable to have a system and method for reducing artifacts in the halftone video thus improving the quality of the video.

SUMMARY OF CERTAIN INVENTIVE ASPECTS

The system, method, and devices of the invention each have several aspects, no single one of which is solely responsible for its desirable attributes. Without limiting the scope of this invention, its more prominent features will now be discussed briefly. After considering this discussion, and particularly after reading the section entitled “Detailed Description of Certain Embodiments” one will understand how the features of this invention provide advantages over other display devices.

In one aspect, a method of processing video data is disclosed. The method comprises generating halftone data for a first video frame and generating halftone data for a second video frame. The method further comprises, to reduce at least one visual artifact, selectively copying the halftone data for the first video frame into the halftone data for the second video frame, the selectively copying being based upon a comparison between an adaptive threshold and the change resulting due to the copying of the data, in the human visual system model based perceptual error of the halftone data for the second video frame.

In another aspect, an apparatus for processing video data is disclosed. The apparatus comprises a memory device having stored therein at least halftone data for a first and second video frame. The apparatus further comprises a processor that is configured to communicate with said memory device and is configured to reduce at least one visual artifact by selectively copying the halftone data for the first video frame into the halftone data for the second video frame, the selectively copying being based upon a comparison between an adaptive threshold and the change, resulting due to this copying of the data, in the human visual system model based perceptual error of the halftone data for the second video frame.

In another aspect, an apparatus for processing video data is disclosed. The apparatus comprises means for generating halftone data for a first video frame and means for generating halftone data for a second video frame. The apparatus further comprises means for reducing at least one visual artifact by selectively copying the halftone data for the first video frame into the halftone data for the second video frame, the selectively copying being based upon a comparison between an adaptive threshold and the change, resulting due to the copying of the data, in the human visual system model based perceptual error of the halftone data for the second video frame.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A and 1B are diagrams illustrating one embodiment of a method of processing halftone video frames to reduce halftone video artifacts.

FIGS. 2A-2B are diagrams illustrating a different embodiment of a method of processing halftone video frames to reduce halftone video artifacts.

FIG. 3 is a flowchart illustrating one embodiment of a method of processing halftone video frames to reduce halftone video artifacts.

FIG. 4 is a flowchart illustrating one embodiment of a method of processing halftone video frames to reduce halftone video artifacts.

FIG. 5 is a diagram illustrating the process of visiting pixels in a frame.

FIG. 6 is a block diagram illustrating one embodiment of an apparatus for processing video data.

DETAILED DESCRIPTION OF CERTAIN EMBODIMENTS

The following detailed description is directed to certain specific embodiments of the invention. However, the invention can be embodied in a multitude of different ways. In this description, reference is made to the drawings wherein like parts are designated with like numerals throughout.

Certain embodiments as will be described below relate to a system and method of processing video data. In one embodiment, a halftone video stream including a sequence of frames is processed to reduce halftone video artifacts under the constraint that the perceptual error between each frame of halftone video and the corresponding frame of continuous-tone video satisfies a criterion. This ensures artifact reduction while preserving the quality of the video. The perceptual error may be estimated based on a human visual system model. Any human visual system model may be used. The perceptual error between a halftone video frame and the corresponding continuous-tone video frame may also be referred to as “the perceptual error of the halftone video frame.”

In one embodiment, the method comprises generating halftone data for a first video frame and generating halftone data for a second video frame. The method further comprises, to reduce at least one visual artifact, selectively copying the halftone data for the first video frame into the halftone data for the second video frame, the selectively copying being based upon a comparison between an adaptive threshold and the change resulting due to the copying of the data, in the human visual system model based perceptual error of the halftone data for the second video frame.

FIGS. 1A and 1B are diagrams illustrating one embodiment of a method of processing halftone video frames to reduce halftone video artifacts. The halftone frames includes a sequence of video frames such as frame X and the next frame in sequence X+1. In one embodiment, the halftone frames are generated by halftoning each frame of the continuous-tone video independently.

In the exemplary embodiment, the method receives a halftone video stream. In another embodiment, the method receives a continuous tone video stream and generate the halftone video stream by halftoning each frame of the continuous-tone video independently.

Each frame includes a set of pixels. Each pixel is referred to by its spatial coordinates (x,y) within the frame. x and y are the horizontal and vertical coordinates as shown. In the exemplary embodiment, the pixel 12 of the frame X may be referred as pixel (1,1). The pixel 14 is at the corresponding location in the frame X+1. In other words, the pixel 14 in the frame X+1 and the pixel 12 in the frame X have the same spatial coordinates in their respective frames. In one embodiment, each pixel may be of one of two values representing bright or dark state when being rendered on a display. A pixel is drawn as a dark box or a white box depending on its pixel value. In FIG. 1A, the pixel 12 has a value representing dark state while the pixel 14 has a value representing bright state.

The halftone frames are duplicated into an output video stream, which is then processed to reduce the halftone artifact. FIG. 1A shows the output video frames X and X+1 before a trial change is made to the pixel 14 in the frame X+1. FIG. 1B shows the output video frames X and X+1 after a trial change is made to the pixel 14 in the frame X+1.

As a part of the process of reducing the halftone artifact, a trial change is made to the pixel 14 in the frame X+1 by copying the value of the pixel 12 in the frame X into the pixel 14 in the frame X+1. After the trial change, FIG. 1B shows that the pixel 14 of the frame X+1 has the same value as the pixel 12 of the frame X. Such trial change could reduce the video artifact such as flickering in the output video stream by improving consistency between neighboring frames.

In one embodiment, to preserve the quality of the output video, a check is then run to ensure that the difference between the perceptual error of the originally generated halftone data for the output video frame X+1 and the perceptual error of the output video frame X+1 after the change, i.e., the frame X+1 shown in FIG. 1B, satisfies a criterion. If the criterion is met, the change to the frame X+1 is kept. Otherwise, the pixel 14 of the frame X+1 is restored to its previous value.

In one embodiment as will be described in regard to FIG. 4, the check is run by comparing, the change in the perceptual error of the halftone video frame X+1 due to the trial change, and an adaptive threshold. The trial change is kept if the change in the perceptual error does not exceed the adaptive threshold.

In one embodiment, all pixels in the frame X+1 are checked in a particular order to see if a value of the corresponding pixel in the frame X should be copied to that pixel, following the same process as described above with regard to the pixel 14. Also, all frames in the output video stream are subject to the same process as described here with regard to the frame X+1.

In the exemplary embodiment, data from a frame X of the output video stream is selectively copied into the next frame X+1 of the output video stream. In another embodiment, data from a frame X of the output video stream may be selectively copied into the frame X−1 of the output video stream, i.e., the frame immediately before the frame X.

In the exemplary embodiment, the value of the pixel (1,1) of a frame X of the output video stream is selectively copied into a pixel of the same spatial coordinates in a neighboring frame of the output video stream.

FIGS. 2A-2B are diagrams illustrating a different embodiment of a method of processing halftone video frames to reduce halftone video artifacts. This embodiment is similar to the embodiment shown in FIG. 1, except when noted otherwise below. FIG. 2A shows the output video frames X and X+1 before a trial change is made to the pixel 18 in the frame X+1. FIG. 2B shows the output video frames X and X+1 after a trial change is made to the pixel 18 in the frame X+1.

As a part of the process of reducing the halftone artifact, the value of the pixel 18 of the frame X+1 of the output video streams is swapped with the value of a neighboring pixel, e.g., the pixel 16 in the same frame as shown. The trial change thus changes the value of the pixel 18 as well as the pixel 16.

In the above FIGS. 1A-2B the principle of various embodiments of a method of processing halftone video frames to reduce halftone video artifacts has been described. Certain exemplary flowcharts will be presented below to illustrate these methods. For illustration purpose, these flowcharts are using the embodiment shown in FIG. 1 as an example, but these flowcharts should not be limited to the method of FIG. 1 only.

FIG. 3 is a flowchart illustrating one embodiment of a method of processing halftone video frames to reduce halftone video artifacts. Depending on the embodiment, certain steps of the method may be removed, merged together, or rearranged in order. The method 30 starts at a block 32, wherein halftone data is generated for a first video frame of a continuous tone video stream. The halftone data may be generated by halftoning the first video frame independently.

The method then moves to a block 34, wherein halftone data is generated for a second video frame of the continuous tone video stream. The halftone data may be generated by halftoning the second video frame independently. The first and the second video frames are next to each other in the continuous tone video stream.

Next, at a block 36, the method selectively, based on an adaptive threshold, includes the halftone data for the first video frame in the halftone data in the second video frame to reduce at least one visual artifact. In one embodiment, the method selectively copies a pixel of the halftone data for the first video frame into the corresponding pixel of the halftone data for the second video frame, if a criterion is met.

As will be further described below in regard to FIG. 4, the selective copying is made if the change in the perceptual error of the second halftone video frame due to the selective copying does not exceed an adaptive threshold. Particularly, the method selectively copies the halftone data for the first video frame into the halftone data for the second video frame wherein the selectively copying is based upon a comparison between an adaptive threshold and the change, resulting due to this copying of the data, in the human visual system model based perceptual error.

In one embodiment, the method may receive the continuous tone video stream and the halftone video stream as input. In that case, the block 34 may be removed.

FIG. 4 is a flowchart illustrating one embodiment of a method of processing halftone video frames to reduce halftone video artifacts. Depending on the embodiment, certain steps of the method may be removed, merged together, or rearranged in order. In the exemplary embodiment, the steps below may be performed by a processor which may be any suitable general purpose single- or multi-chip microprocessor, or any suitable special purpose microprocessor such as a digital signal processor, microcontroller, or a programmable gate array.

The method 40 starts at a block 42, wherein a continuous tone video stream “c” and a halftone video stream “h” are received. The continuous tone video stream c includes a sequence of video frames. The halftone video stream h is the halftone data of the continuous tone video stream c. In one embodiment, the halftone video stream h is produced by halftoning each frame in the continuous tone video stream c independently.

The method then moves to a block 44, wherein an output video stream “o” is generated. It is noted that though the video stream o is called an output video stream, it is for convenience of description. The video stream o is not sent out for display or further processing until the completion of the method 40. The output video stream is the duplicate of the halftone video stream h. A variable “k” is originally set to 1. The variable k is used to indicate which frame in the output video stream is currently under process.

Next, at a decision block 46, the variable k is compared with the number of frames in the halftone video stream h. If the value of k is no less than the number of frames in the halftone video stream h, then all frames have been processed. The method moves to a block 48, in which the method stops and the output video stream o is provided for further image processing or provided to a display for rendering.

Referring again to the decision block 46, if it is determined that the variable k is less than the number of frames in the halftone video stream h, the method moves to a block 52, in which k is increased by 1. At the block 52, a variable “m” is originally set to 1. The variable m is used to indicate how many pixels were copied in one round in which each pixel of the frame k is checked, i.e., in blocks 56-92. In the exemplary embodiment, the variable m is used as an indicator of whether the current frame k has converged to a solution such that the method may move to the next frame. Also, a new variable l is introduced with its value initially set to 0. The variable l is used to track the number of visits to, i.e., tests of pixels of the current frame, i.e., the Kth frame. An adaptive threshold value T₁ is introduced. The threshold T₁ is initialized to an initial value T₀.

Next, at a decision block 54, it is determined whether m equals 0. If m does equal 0, it is determined that no pixel is copied in one round in which each pixel of the frame k is checked. Since no pixel is copied, the method moves to block 46 to process the next frame in the output video stream.

If m does not equal 0, the method then moves to a block 56. At this block, a variable “i” is originally set to 0. The variable i is used to indicate the row coordinate of a pixel currently under process. The variable m is also assigned the value 0.

Moving to a decision block 58, the variable i is compared with the number of rows in the halftone video frame h_(k). If the variable i is not less than the number of rows in the halftone video frame h_(k), then all rows in this frame have been processed, and the method moves to the decision block 54.

Returning again to the decision block 58, if it is determined that the variable i is less than the number of rows in the halftone video frame h_(k), the method moves to a block 62, wherein i is increased by 1 so the method starts processing pixels in the next row. At block 62, a variable “j” is originally set to 0. The variable j is used to indicate the column coordinate of a pixel currently under process.

Moving to a decision block 64, wherein the variable j is compared with the number of columns in the halftone video frame h_(k). If the variable j is no less than the number of columns in the halftone video frame h_(k), then all pixels in row i have been processed. The method moves to the decision block 58. If the variable j is less than the number of columns in the halftone video frame h_(k), then the method moves to a block 66.

At block 66, j is increased by 1 so that the next pixel in row i is under process. The variable l is increased by 1 as the method moves to visit the next pixel.

Next, at a decision block 68, the pixel (i,j) of the kth video frame in the output video stream, which is referred to as o_(k)(i,j) is processed. The value of the pixel o_(k)(i,j) is compared to the value of the pixel (i,j) of the (k−1)th frame in the output video frame o_(k-1), which is referred to as o_(k-1)(i,j). The (k−1)th frame is the frame immediately before the kth frame in the output video stream.

If the pixel o_(k)(i,j) and the pixel o_(k-1)(i,j) have the same value, then the method moves to a block 69, wherein the threshold value T_(l+1) used for the visit of the next pixel remains the same as the current threshold value T_(l). Subsequently, the method moves to the decision block 64 to process the next pixel.

If the pixel o_(k)(i,j) and the pixel o_(k-1)(i,j) do not have the same value, then the method moves to block 72, wherein the value of the pixel o_(k-1)(i,j) is copied into the pixel o_(k)(i,j) for a trial.

Next at a decision block 74, the method evaluates the effect of the trial change made in block 72 so as to decide whether the trial change should be accepted. In the exemplary embodiment, the method determines whether ΔE_(k) _(l) is within an adaptive threshold value T_(l). As will be further explained below, ΔE_(k) _(l) represents the change in the perceptual error of the halftone video frame due to the trial change.

The method then moves to either a block 88 or the block 92, depending on the answer to the inquiry at the decision block 86, to generate the threshold value T_(l+1) used for the visit of the next pixel.

If the answer to the inquiry at block 86 is yes, then the trial change is accepted. The method moves to a block 88, wherein T_(l+1)=T_(l)−ΔE_(k) _(l) . Next at a block 78, the variable m is increased by 1 to indicate that one more pixel copying is made. The method then moves to the decision block 64 to process the next pixel.

If the answer to the inquiry at block 86 is no, then the trial change is not accepted. The method moves to a block 92, wherein the threshold value T_(l+1) used for the visit of the next pixel remains the same as the current threshold value T_(l). Next at a block 76, the value of the pixel o_(k)(i,j) is set back to the value of the pixel h_(k)(i,j), which is the pixel (i,j) of the kth frame in the halftone video stream. The method then moves to the decision block 64 to process the next pixel.

In the exemplary embodiment, the method evaluates the effect of each trial change based on ΔE_(k) _(l) , which represents the change in the perceptual error of the halftone video frame due to the trial change. The perceptual error indicates the difference between the halftone video frame and the continuous-tone video frame as perceived by human vision. Such perceptual error may be calculated based on a model for human visual system (HVS). Any suitable human visual system model may be used.

For the k^(th) halftone frame, h_(k), the corresponding k^(th) error frame is denoted e_(hc,k), with its each pixel e_(hc,k)(i,j) defined by

e_(hc,k)(i,j)≡c_(k)(i,j)−h_(k)(i,j)  Equation 1

The corresponding k^(th) perceived error frame {tilde over (e)}_(hc,k) is then defined as

{tilde over (e)}_(hc,k)≡e_(hc,k)*{tilde over (p)}  Equation 2

Here * indicates 2-dimensional convolution, and {tilde over (p)} is a point spread function representing a model of the human visual system. In the exemplary embodiment, the point spread function is determined by a luminance spatial frequency response function as proposed by R. Nasanen, “Visibility of halftone dot textures”, IEEE Trans. Syst. Man. Cyb., vol. 14, no. 6, pp. 920-924, 1984. However, other human visual system models may also be used.

The perceptual error between h_(k) and c_(k) is defined as

$\begin{matrix} {E_{{hc},k} \equiv {\sum\limits_{i = 1}^{M}{\sum\limits_{j = 1}^{N}{\overset{\sim}{e}}_{{hc},k}^{2}}}} & {{Equation}\mspace{14mu} 3} \end{matrix}$

Similarly, for the k^(th) output frame, o_(k), the corresponding k^(th) error frame is denoted o_(hc,k), with its each pixel o_(hc,k)(i,j) defined by

o_(hc,k)(i,j)=c_(k)(i,j)−o_(k)(i,j)  Equation 4

The corresponding k^(th), perceived error frame {tilde over (e)}_(oc,k) is then defined as

{tilde over (e)}_(oc,k)≡e_(oc,k)*{tilde over (p)}  Equation 5

the perceptual error between o_(k) and c_(k) is defined as

$\begin{matrix} {E_{{oc},k} \equiv {\sum\limits_{i = 1}^{M}{\sum\limits_{j = 1}^{N}{\overset{\sim}{e}}_{{oc},k}^{2}}}} & {{Equation}\mspace{14mu} 6} \end{matrix}$

The change in the perceptual error of the halftone video frame due to the trial change, as represented by ΔE_(k) _(l) , may be determined in the following Equations.

ΔE_(k) _(l) =E_(oc,k) _(l) −E_(hc,k) for l=1  Equation 7

ΔE_(k) _(l) =E_(oc,k) _(l-1) for otherwise  Equation 8

Wherein M is the number of rows and N is the number of columns in the current frame K. E_(hc,k) is as defined in Equation 3. E_(oc,k) _(l-1) represents the perceptual error between the output frame o_(k) _(l-1) and c_(k) and E_(oc,k) _(l) represents the perceptual error between the output frame and c_(k) _(l) and c_(k), o_(k) _(l) is the kth video frame in the output video stream after its pixels are visited 1 times.

As shown above, the adaptive threshold value T_(l) can be calculated as follows.

T₁=T₀, where T₀ is the initial threshold value  Equation 9

T_(l+1)=T₁−ΔE_(k) _(l) , if the trial change is accepted  Equation 10

T_(l+1)=T_(l), if the trial change is not accepted or if no trial change can be made  Equation 11

In the exemplary embodiment, the method evaluates the effect of each trial change by calculating the change in the perceptual error of the halftone video frame due to the trial change. The exemplary embodiment is more computationally efficient over an alternative approach which includes, each time a trial change is made to a halftone video frame, recalculating the difference in the perceptual error of the originally generated halftone video frame and the perceptual error of the halftone video frame after a trial change.

In the embodiment as presented in FIG. 4, the metric E_(oc,k)−E_(hc,k) only needs to be calculated once with each frame when the method visits the first pixel of the frame. When the method moves from a pixel X to the next pixel X+1, the method only needs to calculate ΔE_(k) _(l) =E_(oc,k) _(l) E_(oc,k) _(l-1) , which is simple to calculate since the frame o_(k) _(l-1) and the frame o_(k) _(l) are different only in the pixel X+1.

In the above flowchart, the output video stream is processed beginning from the second frame to the last frame of the output video stream. When a frame X is under process, each round all pixels within the frame are checked one by one to test if a change to the pixel value may be made. If no pixel is changed within one round, the method moves to the next frame. In the exemplary embodiment, the pixels in the frame X are processed in a raster scanning order, i.e., beginning from top to bottom and from left to right. The pixels in a row Y are processed before pixels in a row immediately below the row Y. Within the row Y, a pixel Z is processed before the pixel next to the pixel Z on the right side. For each pixel of the frame X, it is determined whether a value of the pixel at the corresponding location in the frame immediately before the frame X may be copied and whether the perceptual error between the output video frame X and the continuous-tone video frame X still remains within a threshold with such a change. The change is kept if the perceptual error remains within the threshold.

In the exemplary embodiment, the pixels within a frame are processed according to the raster scanning order. It should be noted that the pixels may be processed in any other order. In the exemplary embodiment, the method moves to the next frame if no pixel is changed within one round in which all pixels of a frame are checked once. It should be noted that in another embodiment, the method moves to the next frame if the number of changes made within one round satisfies a certain criterion, e.g., if the changes made within one round are less than three times.

FIG. 5 is a diagram illustrating the process of visiting pixels in a frame. Frames 102, 112, 122, 132, and 142 are used to represent different versions of the frame K in the output video stream.

In the example, the method starts to visit the first pixel, i.e., the pixel 104, of the frame 102 to check if a trial change to the pixel 104 should be made. The variable l is set as 1. The frame 102, which is also referred to as K₁, represents the frame K before the trial change is made.

The method then moves to the next pixel, i.e., the pixel 114. The frame 112, which is also referred to as K₂, represents the frame K after the processing of the pixel 104 is completed and before the trial change is made to the pixel 114.

The method then moves to the next pixel, i.e., the pixel 124. The frame 122, which is also referred to as K₃, represents the frame K after the processing of the pixel 114 is completed and before the trial change is made to the pixel 124.

This process continues until the method tests the last pixel in the frame K, i.e., the pixel 134 in the frame 132, i.e., the frame K₉. The variable l is increased to 9.

Depending on whether any test changes are accepted in this round visiting all pixels of the K frame, the method may continue to visit the first pixel of the K frame, i.e., the pixel 144 in the frame 142. The variable l is increased to 10. And the output K frame 142 is referred to as K₁₀.

FIG. 6 is a block diagram illustrating one embodiment of an apparatus for processing video data. In the exemplary embodiment, the apparatus 160 receives a continuous tone video stream as video input and then provides a processed video stream to a display 166. In another embodiment, the processed video stream as provided by the apparatus 160 may be subject to further video processing before being provided to the display 166.

In the exemplary embodiment, the apparatus 160 includes a memory device 164 which stores the continuous tone video stream and the corresponding halftone video stream as discussed above. The memory device 164 may also store other data and any software modules to be executed. The memory device 164 may be any type of storage media suitable for this purpose.

The apparatus 160 may further include a control unit 162 configured to communicate with the memory device and to perform the methods for processing video data as described above. In the exemplary embodiment, the control unit may be processor which may be any general purpose single- or multi-chip microprocessor such as an ARM, Pentium®, Pentium II®, Pentium III®, Pentium IV®, Pentium® Pro, an 8051, a MIPS®, a Power PC®, an ALPHA®, or any special purpose microprocessor such as a digital signal processor, microcontroller, or a programmable gate array. As is conventional in the art, the processor may be configured to execute one or more software modules. In addition to executing an operating system, the processor may be configured to execute one or more software applications.

In the exemplary embodiment, the apparatus 160 receives the continuous tone video stream and generates halftone data for the continuous tone video stream as described above. In another embodiment, the apparatus 160 may receive both the continuous tone video stream and the corresponding halftone video stream. In one embodiment, the halftone video stream is generated by halftoning each frame of the continuous tone video stream independently.

The display 166 may be any device that is configured to display an image, whether in motion (e.g., video) or stationary (e.g., still image), and whether textual or pictorial. More particularly, it is contemplated that the embodiments may be implemented in or associated with a variety of electronic devices such as, but not limited to, mobile telephones, wireless devices, personal data assistants (PDAs), hand-held or portable computers, GPS receivers/navigators, cameras, MP3 players, camcorders, game consoles, wrist watches, clocks, calculators, television monitors, flat panel displays, computer monitors, auto displays (e.g., odometer display, etc.), cockpit controls and/or displays, display of camera views (e.g., display of a rear view camera in a vehicle), electronic photographs, electronic billboards or signs, projectors, architectural structures, packaging, and aesthetic structures (e.g., display of images on a piece of jewelry).

In one embodiment, the display may be any binary display. In another embodiment, the display may be an interferometric modulator display. In an interferometric modulator display, the pixels are in either a bright or dark state. In the bright (“on” or “open”) state, the display element reflects a large portion of incident visible light to a user. When in the dark (“off” or “closed”) state, the display element reflects little incident visible light to the user. Depending on the embodiment, the light reflectance properties of the “on” and “off” states may be reversed. These pixels can be configured to reflect predominantly at selected colors, allowing for a color display in addition to black and white.

In one embodiment of the interferometric modulator display, each pixel comprises a Microelectromechanical systems (MEMS) interferometric modulator. In some embodiments, an interferometric modulator display comprises a row/column array of these interferometric modulators. Each interferometric modulator includes a pair of reflective layers positioned at a variable and controllable distance from each other to form a resonant optical gap with at least one variable dimension. In one embodiment, one of the reflective layers may be moved between two positions. In the first position, referred to herein as the relaxed position, the movable reflective layer is positioned at a relatively large distance from a fixed partially reflective layer. In the second position, referred to herein as the actuated position, the movable reflective layer is positioned more closely adjacent to the partially reflective layer. Incident light that reflects from the two layers interferes constructively or destructively depending on the position of the movable reflective layer, producing either an overall reflective or non-reflective state for each pixel.

The foregoing description details certain embodiments of the invention. It will be appreciated, however, that no matter how detailed the foregoing appears in text, the invention can be practiced in many ways. It should be noted that the use of particular terminology when describing certain features or aspects of the invention should not be taken to imply that the terminology is being re-defined herein to be restricted to including any specific characteristics of the features or aspects of the invention with which that terminology is associated. 

1. A method of processing video data, comprising: generating halftone data for a first video frame; generating halftone data for a second video frame; and to reduce at least one visual artifact, selectively copying the halftone data for the first video frame into the halftone data for the second video frame, the selectively copying being based upon a comparison between an adaptive threshold and the change resulting due to the copying of the data, in a human visual system model-based perceptual error of the halftone data for the second video frame.
 2. The method of claim 1, wherein selectively copying the generated halftone data further comprises: generating output data for the first frame, the output data for the first frame equal to the halftone data for the first frame; generating output data for the second frame, the output data for the second frame equal to the halftone data for the second frame; and to reduce at least one visual artifact, selectively copying the output data for the first video frame into the output data for the second video frame, the selectively copying being based upon a comparison between an adaptive threshold and the change, resulting due to the copying of the data, in the human visual system model-based perceptual error of the output data for the second video frame.
 3. The method of claim 2, wherein selectively copying the output data comprises selectively copying a value of a pixel in the output data for the first video frame into the corresponding location in the output data for the second video frame, the selectively copying being based upon a comparison between an adaptive threshold and the change, resulting due to this copying of the data, in the human visual system model-based perceptual error of the output data for the second video frame.
 4. The method of claim 3, wherein the pixel in the output data for the second video frame is located at a location corresponding to the location of the pixel in the output data for the first video frame.
 5. The method of claim 3, wherein selectively copying a value of a pixel in the output data for the first video frame comprises scanning each pixel in the output data for the second video frame and selectively copying the pixel in the output data for the first video frame into a pixel in the output data for the second video frame, the selectively copying being based upon a comparison between an adaptive threshold and the change, resulting due to this copying of the data, in the human visual system model-based perceptual error of the output data for the second video frame.
 6. The method of claim 5, wherein scanning each pixel in the output data for the second video frame and selectively copying the pixel in the output data for the first video frame is repeated until the number of copying made during a previous round of scanning meets a predetermined criterion.
 7. The method of claim 6, wherein scanning each pixel in the output data for the second video frame and selectively copying of the pixel in the output data for the first video frame is repeated until no copying is made during a previous round of scanning.
 8. The method of claim 5, wherein the pixels in the output data for the second video frame are processed in a raster scan order starting from top to bottom and from left to right.
 9. The method of claim 1, wherein the visual artifact comprises flicker.
 10. The method of claim 1, wherein the video data comprises a time sequence of video frames comprising the first and second video frame.
 11. The method of claim 1, wherein the first video frame immediately precedes the second video frame.
 12. The method of claim 1, wherein the first video frame is the next frame after the second video frame.
 13. The method of claim 1, wherein selectively copying the generated halftone data further comprises selectively copying the halftone data for the first video frame into the halftone data for the second video frame based upon a comparison between an adaptive threshold and the change, resulting due to the copying of the data, in the human visual system model-based perceptual error of the halftone data for the second video frame, the adaptive threshold varying in response to previous modification made to the generated halftone data for the second video frame.
 14. An apparatus for processing video data, comprising: a memory device having stored therein at least halftone data for a first and second video frame; and a processor that is configured to communicate with said memory device and is configured to reduce at least one visual artifact by selectively copying the halftone data for the first video frame into the halftone data for the second video frame, the selectively copying being based upon a comparison between an adaptive threshold and the change, resulting due to this copying of the data, in a human visual system model-based perceptual error of the halftone data for the second video frame.
 15. An apparatus for processing video data, comprising: means for generating halftone data for a first video frame; means for generating halftone data for a second video frame; and means for reducing at least one visual artifact by selectively copying the halftone data for the first video frame into the halftone data for the second video frame, the selectively copying being based upon a comparison between an adaptive threshold and the change, resulting due to the copying of the data, in a human visual system model-based perceptual error of the halftone data for the second video frame. 